TSNE-CUDA is an optimized CUDA version of FIt-SNE algorithm with associated python modules. We find that our implementation of t-SNE can be up to 1200x faster than Sklearn, or up to 50x faster than Multicore-TSNE when used with the right GPU. The paper describing our approach, as well as the results below, is available at


ustat is a micro-statistics program (like ministat) written in Rust which computes the sum, mean, median, min, max, standard deviation and a one-way ANOVA of a set of input files.